Learning Nuclear Structure with AI: Radii and Collectivity
Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides. Learning how this information is organized across observables and nuclei can provide a data-driven empirical baseline for theoretical extrapolations and experimental design. Here, we develop held-out ensemb...
G. Giacalone, S. Trifinopoulos, Mike Williams
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